This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14-17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.

The Pattern Recognition in Bioinformatics (PRIB) meeting was established in 2006 under the auspices of the International Association for Pattern Recognition (IAPR) to create a focus for the development and application of pattern recognition techniques in the biological domain. PRIB's aim to explore the full spectrum of pattern recognition application was re?ected in the breadth of techniquesrepresented in this year's subm- sions and in this book. These range from image analysis for biomedical data to systems biology. We werefortunatetohaveinvitedspeakersofthehighestcalibredeliveringkeynotes at the conference. These were Pierre Baldi (UC Irvine), Alvis Brazma (EMBL-EBI), GunnarRats .. ch(MPITubi .. ngen)andMichaelUnser(EPFL).Weacknowledgesupportof theEUFP7NetworkofExcellencePASCAL2forpartiallyfundingtheinvitedspeakers. Immediately prior to the conference, we hosted half day of tutorial lectures, while a special session on "Machine Learningfor IntegrativeGenomics" was held immediately after the main conference.Duringthe conference,a poster session was heldwith further discussion. Wewouldlikeonceagaintothankalltheauthorsforthehighqualityofsubmissions, as well as Yorkshire South and the University of Shef?eld for providing logistical help in organizing the conference. Finally, we would like to thank Springer for their help in assembling this proceedings volume and for the continued support of PRIB.

Biometrics is a rapidly evolving field with applications ranging from accessing one 's computer to gaining entry into a country. The deployment of large-scale biometric systems in both commercial and government applications has increased public awareness of this technology. Recent years have seen significant growth in biometric research resulting in the development of innovative sensors, new algorithms, enhanced test methodologies and novel applications. This book addresses this void by inviting some of the prominent researchers in Biometrics to contribute chapters describing the fundamentals as well as the latest innovations in their respective areas of expertise.

This book constitutes the refereed proceedings of the 7th International Conference on Computer Vision Systems, ICVS 2009, held in Liege, Belgium, October 13-15, 2009.

The 21 papers for oral presentation presented together with 24 poster presentations and 2 invited papers were carefully reviewed and selected from 96 submissions. The papers are organized in topical sections on human-machine-interaction, sensors, features and representations, stereo, 3D and optical flow, calibration and registration, mobile and autonomous systems, evaluation, studies and applications, learning, recognition and adaption.

Privacy, Security and Trust within the Context of Pervasive Computing is an edited volume based on a post workshop at the second international conference on Pervasive Computing. The workshop was held April18-23, 2004, in Vienna, Austria.

The goal of the workshop was not to focus on specific, even novel mechanisms, but rather on the interfaces between mechanisms in different technical and social problem spaces. An investigation of the interfaces between the notions of context, privacy, security, and trust will result in a deeper understanding of the "atomic" problems, leading to a more complete understanding of the social and technical issues in pervasive computing.

Starting with fingerprints more than a hundred years ago, there has been ongoing research in biometrics. Within the last forty years face and speaker recognition have emerged as research topics. However, as recently as a decade ago, biometrics itself did not exist as an independent field. Each of the biometric-related topics grew out of different disciplines. For example, the study of fingerprints came from forensics and pattern recognition, speaker recognition evolved from signal processing, the beginnings of face recognition were in computer vision, and privacy concerns arose from the public policy arena. One of the challenges of any new field is to state what the core ideas are that define the field in order to provide a research agenda for the field and identify key research problems. Biometrics has been grappling with this challenge since the late 1990s. With the matu ration of biometrics, the separate biometrics areas are coalescing into the new discipline of biometrics. The establishment of biometrics as a recognized field of inquiry allows the research community to identify problems that are common to biometrics in general. It is this identification of common problems that will define biometrics as a field and allow for broad advancement."

Model Based Fuzzy Control uses a given conventional or fuzzy open loop model of the plant under control to derive the set of fuzzy rules for the fuzzy controller. Of central interest are the stability, performance, and robustness of the resulting closed loop system. The major objective of model based fuzzy control is to use the full range of linear and nonlinear design and analysis methods to design such fuzzy controllers with better stability, performance, and robustness properties than non-fuzzy controllers designed using the same techniques. This objective has already been achieved for fuzzy sliding mode controllers and fuzzy gain schedulers - the main topics of this book. The primary aim of the book is to serve as a guide for the practitioner and to provide introductory material for courses in control theory.

This book introduces the area of image processing and data-parallel processing. It covers a number of standard algorithms in image processing and describes their parallel implementation. The programming language chosen for all examples is a structured parallel programming language which is ideal for educational purposes. It has a number of advantages over C, and since all image processing tasks are inherently parallel, using a parallel language for presentation actually simplifies the subject matter. This results in shorter source codes and a better understanding. Sample programs and a free compiler are available on an accompanying Web site.

Humans have always been hopeless at predicting the future...most people now generally agree that the margin of viability in prophecy appears to be 1 ten years. Even sophisticated research endeavours in this arena tend to go 2 off the rails after a decade or so. The computer industry has been particularly prone to bold (and often way off the mark) predictions, for example: 'I think there is a world market for maybe five computers' Thomas J. Watson, IBM Chairman (1943), 'I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won't last out the year' Prentice Hall Editor (1957), 'There is no reason why anyone would want a computer in their home' Ken Olsen, founder of DEC (1977) and '640K ought to be enough for anybody' Bill Gates, CEO Microsoft (1981). 3 The field of Artificial Intelligence - right from its inception - has been particularly plagued by 'bold prediction syndrome', and often by leading practitioners who should know better. AI has received a lot of bad press 4 over the decades, and a lot of it deservedly so. How often have we groaned in despair at the latest 'by the year-20xx, we will all have...(insert your own particular 'hobby horse' here - e. g.

Computer security - the protection of data and computer systems from intentional, malicious intervention - is attracting increasing attention. Much work has gone into development of tools to detect ongoing or already perpetrated attacks, but a key shortfall in current intrusion detection systems is the high number of false alarms they produce. This book analyzes the false alarm problem, then applies results from the field of information visualization to the problem of intrusion detection. Four different visualization approaches are presented, mainly applied to data from web server access logs.

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-a-vis several widely used classifiers, including neural networks. "

This textbook is for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities: sampling, measurement and inference. The monograph aims to prepare the reader for the career of an independent social statistician and to serve as a reference for methods, ideas for and ways of studying of human populations. Elementary linear algebra and calculus are prerequisites, although the exposition is quite forgiving. Familiarity with statistical software at the outset is an advantage, but it can be developed while reading the first few chapters.

A sharp increase in the computing power of modern computers has triggered the development of powerful algorithms that can analyze complex patterns in large amounts of data within a short time period. Consequently, it has become possible to apply pattern recognition techniques to new tasks. The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.

The Annual (ICGS) International Conference is an established platform in which se- rity, safety and sustainability issues can be examined from several global perspectives through dialogue between academics, students, government representatives, chief executives, security professionals, and research scientists from the United Kingdom and from around the globe. The 2009 two-day conference focused on the challenges of complexity, rapid pace of change and risk/opportunity issues associated with modern products, systems, s- cial events and infrastructures. The importance of adopting systematic and systemic approaches to the assurance of these systems was emphasized within a special stream focused on strategic frameworks, architectures and human factors. The conference provided an opportunity for systems scientists, assurance researchers, owners, ope- tors and maintainers of large, complex and advanced systems and infrastructures to update their knowledge with the state of best practice in these challenging domains while networking with the leading researchers and solution providers. ICGS3 2009 received paper submissions from more than 20 different countries around the world. Only 28 papers were selected and were presented as full papers. The program also included three keynote lectures by leading researchers, security professionals and government representatives. June 2009 Hamid Jahankhani Ali Hessami Feng Hsu

This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.

Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. This book presents novel applications and real world applications working in Manufacturing and Engineering, and it sets a basis for understanding Domotic and Production Methods of the XXI Century.

This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers' tuning processes and enhance the performance of their control systems. It further contains application examples.

This book brings all the major and frontier topics in the field of document analysis together into a single volume, creating a unique reference source that will be invaluable to a large audience of researchers, lecturers and students working in this field. With chapters written by some of the most distinguished researchers active in this field, this book addresses recent advances in digital document processing research and development.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Computer Vision and Graphics, ICCVG 2008, held in Warsaw, Poland, in November 2008.

The 48 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on image processing, image quality assessment, geometrical models of objects and scenes, motion analysis, visual navigation and active vision, image and video coding, virtual reality and multimedia applications, biomedical applications, practical applications of pattern recognition, computer animation, visualization and graphical data presentation.

One of the grand challenges for computational intelligence and biometrics is to understand how people process and recognize faces and to develop automated and reliable face recognition systems. Biometrics has become the major component in the complex decision making process associated with security applications. The many challenges addressed for face detection and authentication include cluttered environments, occlusion and disguise, temporal changes, and last but not least, robust training and open set testing.

Reliable Face Recognition Methods seeks to comprehensively address the face recognition problem while drawing inspiration and gaining new insights from complementary fields of endeavor such as neurosciences, statistics, signal and image processing, computer vision, and machine learning and data mining. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future R&D.

With its well-focused approach and clarity of presentation, this new text/reference is an excellent resource for computer scientists and engineers, researchers, and professionals who need to learn about face recognition. In addition, the book is ideally suited to students studying biometrics, pattern recognition, and human-computer interaction.

Noisy data appear very naturally in applications where the authentication is based on physical identifiers. This book provides a self-contained overview of the techniques and applications of security based on noisy data. It provides a comprehensive overview of the theory of extracting cryptographic keys from noisy data, and describes applications in the field of biometrics, secure key storage, and anti-counterfeiting.

The evolution of technology has set the stage for the rapid growth of the video Web: broadband Internet access is ubiquitous, and streaming media protocols, systems, and encoding standards are mature. In addition to Web video delivery, users can easily contribute content captured on low cost camera phones and other consumer products. The media and entertainment industry no longer views these developments as a threat to their established business practices, but as an opportunity to provide services for more viewers in a wider range of consumption contexts. The emergence of IPTV and mobile video services offers unprecedented access to an ever growing number of broadcast channels and provides the flexibility to deliver new, more personalized video services. Highly capable portable media players allow us to take this personalized content with us, and to consume it even in places where the network does not reach. Video search engines enable users to take advantage of these emerging video resources for a wide variety of applications including entertainment, education and communications. However, the task of information extr- tion from video for retrieval applications is challenging, providing opp- tunities for innovation. This book aims to first describe the current state of video search engine technology and second to inform those with the req- site technical skills of the opportunities to contribute to the development of this field. Today's Web search engines have greatly improved the accessibility and therefore the value of the Web.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2009, held at the University of Iceland, Reykjavik, Iceland in June 2009. Being the eighth in a well-established series of meetings providing an inter- tional forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern recognition, machine learning and stat- tics) concerned with this research topic. From more than 70 submissions, the Program Committee selected 54 papers to create an interesting scienti?c program. The special focus of MCS 2009 was on the application of multiple classi?er systems in remote sensing. This part- ular application uses multiple classi?ers for raw data fusion, feature level fusion and decision level fusion. In addition to the excellent regular submission in the technical program, outstanding contributions were made by invited speakers Melba Crawford from Purdue University and Zhi-Hua Zhou of Nanjing Univ- sity. Papers of these talks are included in these workshop proceedings. With the workshop'sapplicationfocusbeingonremotesensing, Prof.Crawford'sexpertise in the use of multiple classi?cation systems in this context made the discussions on this topic at MCS 2009 particularly fruitful.

This book constitutes the refeered proceedings of the 21st International Conference on Information Processing in Medical Imaging, IPMI 2009, held in Williamsburg, VA, USA, in July 2009

The 26 revised full papers and 33 revised poster papers presented were carefully reviewed and selected from 150 submissions. The papers are organized in topical sections on diffusion imaging, PET imaging, image registration, functional networks, space curves, tractography, microscopy, exploratory analyses, features and detection, image guided surgery, shape analysis, motion, and segmentation and validation.

Correlation is a robust and general technique for pattern recognition and is used in many applications, such as automatic target recognition, biometric recognition and optical character recognition. The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing. This book provides a needed review of this diverse background material and develops the signal processing theory, the pattern recognition metrics, and the practical application know-how from basic premises. It shows both digital and optical implementations. It also contains state-of-the-art technology presented by the team that developed it and includes case studies of significant current interest, such as face and fingerprint recognition. Suitable for advanced undergraduate or graduate students taking courses in pattern recognition theory, whilst reaching technical levels of interest to the professional practitioner.